code: def test_partial_schedule(self):
      scheduler = self.get_scheduler()
      assert isinstance(scheduler, CombinedLearningRateScheduler)
      assert isinstance(scheduler._current_scheduler, PolynomialDecay)
  
      # This should be 0 because the PolynomialDecay scheduler initializes the LR to 0.
      assert self.optimizer.param_groups[0]["lr"] == 0.0
  
      epoch_end_lrs = []
      for epoch in range(10):
          if epoch > 6:
              assert scheduler._current_scheduler is None
          elif epoch >= 2:
              assert scheduler._current_scheduler is not None
              assert scheduler._current_scheduler.total_steps == 50
              assert scheduler._current_scheduler.base_values[0] == 0.5
          else:
              assert scheduler._current_scheduler is not None
              assert scheduler._current_scheduler.total_steps == 20
              assert scheduler._current_scheduler.base_values[0] == 1.0
  
          for step in range(10):
              scheduler.step_batch()
  
          scheduler.step()
  
          epoch_end_lrs.append(self.optimizer.param_groups[0]["lr"])
  
      assert epoch_end_lrs[0] == 1.0
      assert epoch_end_lrs[1] == 0.5
      assert epoch_end_lrs[6] == 0.1
      assert epoch_end_lrs[6] == 0.1
  
file_path: allennlp/tests/training/learning_rate_schedulers/combined_test.py
imports: import torch
  from allennlp.common.testing import AllenNlpTestCase
  from allennlp.common.params import Params
  from allennlp.training.learning_rate_schedulers import LearningRateScheduler, CombinedLearningRateScheduler, PolynomialDecay
  from allennlp.training.optimizers import Optimizer
label_desc: Use image node_id 3 for calling the TestCombinedLRScheduler obj's underlying member method code with example usage: obj.test_partial_schedule() without return types